code: def test_numpy_lstsq(
      x,
      y,
      frontend,
      test_flags,
      fn_tree,
      backend_fw,
      on_device,
  ):
      dtype1, a, _ = x
      dtype2, b = y
      ret, ret_gt = helpers.test_frontend_function(
          input_dtypes=[dtype1, dtype2],
          frontend=frontend,
          test_flags=test_flags,
          backend_to_test=backend_fw,
          fn_tree=fn_tree,
          on_device=on_device,
          a=a,
          b=b,
          test_values=False,
      )
      for ret_f, ret_gtt in zip(ret, ret_gt):
          # TODO: Uncomment this once the function is implemented on the API side
          # frontend_ret = ret_f
          # frontend_ret_gt = ret_gt
          # ret_flattened = helpers.flatten_and_to_np(ret=frontend_ret)
          # ret_gt_flattened = helpers.flatten_fw_and_to_np(
          #       ret=frontend_ret_gt, fw="numpy")
          # helpers.value_test(
          #     ret_np_flat=ret_flattened,
          #     ret_np_from_gt_flat=ret_gt_flattened,
          #     ground_truth_backend="numpy",
          # )
          return
  
file_path: ivy/ivy_tests/test_ivy/test_frontends/test_numpy/test_linalg/test_solving_equations_and_inverting_matrices.py
imports: import sys
  import numpy
  from hypothesis import strategies, assume
  import ivy_tests.test_ivy.helpers
  from ivy_tests.test_ivy.helpers import handle_frontend_test
label_desc: Use image node_id 3 for calling a global function with example usage: test_numpy_lstsq(x, y, frontend, test_flags, fn_tree, backend_fw, on_device) without return types